Probabilistic evaluation of the hosting capacity in distribution networks

To correctly estimate the hosting capacity, the proposed approach has been designed as the basis of a tool to analyze the scalability and replicability potential of smart grids solution. The paper is devoted to the hosting capacity evaluation of distribution feeders with the three step probabilistic approach. The proposed method is presented and applied to a medium voltage network with 8 feeders.

[1]  Martin Braun,et al.  Twilight of the Grids: The Impact of Distributed Solar on Germany?s Energy Transition , 2015, IEEE Power and Energy Magazine.

[2]  Igor Papic,et al.  Assessment of maximum distributed generation penetration levels in low voltage networks using a probabilistic approach , 2015 .

[3]  Fainan Hassan,et al.  Integration of Distributed Generation in the Power System: Bollen/Integration of Distributed Generation , 2011 .

[4]  Brian Seal,et al.  Smart inverter volt/var control functions for high penetration of PV on distribution systems , 2011, 2011 IEEE/PES Power Systems Conference and Exposition.

[5]  Roman Schwalbe,et al.  DG DemoNet validation: Voltage control from simulation to field test , 2011, 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies.

[6]  Andreas Abart,et al.  Local Voltage Control by PV Inverters: First Operating Experience from Simulation, Laboratory Tests and Field Tests , 2012 .

[7]  Jay Johnson,et al.  Lab Tests: Verifying That Smart Grid Power Converters Are Truly Smart , 2015, IEEE Power and Energy Magazine.

[8]  T. Stetz,et al.  Improved Low Voltage Grid-Integration of Photovoltaic Systems in Germany , 2013, IEEE Transactions on Sustainable Energy.

[9]  Achilleas Tsitsimelis,et al.  ON THE DER HOSTING CAPACITY OF DISTRIBUTION FEEDERS , 2015 .

[10]  Andreas Abart,et al.  Evaluation of Voltage Control Algorithms in Smart Grids: Results of the Project: morePV2grid , 2014 .

[11]  P. Rodriguez,et al.  Local Reactive Power Control Methods for Overvoltage Prevention of Distributed Solar Inverters in Low-Voltage Grids , 2011, IEEE Journal of Photovoltaics.

[12]  Andreas Abart,et al.  The Best of IGREENGrid Practices: A Distribution Network's Contribution to Resiliency , 2015, IEEE Power and Energy Magazine.

[13]  Roman Schwalbe,et al.  Controlling active low voltage distribution grids with minimum efforts on costs and engineering , 2013, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society.

[14]  Enrico Zio,et al.  Monte Carlo Simulation-Based Probabilistic Assessment of DG Penetration in Medium Voltage Distribution Networks , 2015 .

[15]  Achim Woyte,et al.  Development of innovative voltage control for distribution networks with high photovoltaic penetration , 2012 .

[16]  N.D. Hatziargyriou,et al.  Voltage control settings to increase wind power based on probabilistic load flow , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[17]  Martin Braun,et al.  Techno-Economic Assessment of Voltage Control Strategies in Low Voltage Grids , 2014, IEEE Transactions on Smart Grid.

[18]  Math Bollen,et al.  Voltage control in distribution systems as a limitation of the hosting capacity for distributed energy resources , 2005 .

[19]  R Tonkoski,et al.  Coordinated Active Power Curtailment of Grid Connected PV Inverters for Overvoltage Prevention , 2011, IEEE Transactions on Sustainable Energy.

[20]  Math Bollen,et al.  Integration of Distributed Generation in the Power System , 2008 .

[21]  J.H. Zhang,et al.  Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Cholesky Decomposition , 2009, IEEE Transactions on Power Systems.